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Reproducibility of Left Ventricular Dimension Versus Area Versus Volume Measurements in Pediatric Patients With Dilated Cardiomyopathy

2017· article· en· W2769550667 on OpenAlexafffund
Elif Seda Selamet Tierney, Danielle Hollenbeck-Pringle, Caroline K. Lee, Karen Altmann, Carolyn Dunbar‐Masterson, Fraser Golding, Minmin Lü, Stephen G. Miller, Kimberly Molina, Shobha Natarajan, Carolyn L. Taylor, Felicia Trachtenberg, Steven D. Colan

Bibliographic record

VenueCirculation Cardiovascular Imaging · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersNational Heart, Lung, and Blood InstituteHospital for Sick ChildrenNew England Research InstitutesNational Center for Research ResourcesUniversity of South CarolinaChildren's Hospital of PhiladelphiaEast Carolina UniversityUniversity of UtahWake Forest University
KeywordsReproducibilityMedicineDilated cardiomyopathyEjection fractionCardiologyStroke volumeVentricular volumeSonographerInternal medicineCardiomyopathyNuclear medicineRadiologyHeart failureUltrasound

Abstract

fetched live from OpenAlex

Background— Multiple echocardiographic methods are used to measure left ventricular size and function. Clinical management is based on individual evaluations and longitudinal trends. The Pediatric Heart Network VVV study (Ventricular Volume Variability) in pediatric patients with dilated cardiomyopathy has reported reproducibility of several of these measures, and how disease state and number of beats impact their reproducibility. In this study, we investigated the impact of observer and sonographer variation on reproducibility of dimension, area, and volume methods to determine the best method for both individual and sequential evaluations. Methods and Results— In 8 centers, echocardiograms were obtained on 169 patients prospectively. During the same visit, 2 different sonographers acquired the same imaging protocol on each patient. Each acquisition was analyzed by 2 different observers; first observer analyzed the first acquisition twice. Intraobserver, interobserver, interacquisition, and interobserver-acquisition (different observers and different acquisition) reproducibility were assessed on measurements of left ventricular end-diastolic dimension, area, and volume. Left ventricular shortening fraction, ejection fraction, mass, and fractional area change were calculated. Percent difference was calculated as (interobservation difference/mean)×100. Interobserver reproducibility for both acquisitions was better for both volume and dimension measurements ( P ≤0.002) compared with area measurements, whereas intraobserver, interacquisition (for both observers), and interobserver-acquisition reproducibilities (for both observer-acquisition sets) were best for volume measurements ( P ≤0.01). Overall, interobserver-acquisition percent differences were significantly higher than interobserver and interacquisition percent differences ( P <0.001). Conclusions— In pediatric patients with dilated cardiomyopathy, compared with dimension and area methods, left ventricular measurements by volume method have the best reproducibility in settings where assessment is not performed by the same personnel. Clinical Trial Registration— URL: https://www.clinicaltrials.gov . Unique identifier: NCT00123071.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.249
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainMethods
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations17
Published2017
Admission routes2
Has abstractyes

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